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Objective: Post-stroke cognitive impairment is common, but mechanisms and risk factors are poorly understood. Frailty may be an important risk factor for cognitive impairment after stroke. We investigated the association between pre-stroke frailty and acute post-stoke cognition. Methods: We studied consecutively admitted acute stroke patients in a single urban teaching hospital during three recruitment waves between May 2016 and December 2017. Cognition was assessed using the Mini-Montreal Cognitive Assessment (min=0; max=12). A Frailty Index was used to generate frailty scores for each patient (min=0; max=100). Clinical and demographic information were collected, including pre-stroke cognition, delirium, and stroke-severity. We conducted univariate and multiple-linear regression analyses with covariates forced in (covariates included were: age, sex, stroke severity, stroke-type, pre-stroke cognitive impairment, delirium, previous stroke/transient ischemic attack) to investigate the association between pre-stroke frailty and post-stroke cognition. Results: Complete data were available for 154 stroke patients. Mean age was 68 years (SD=11; range=32–97); 93 (60%) were male. Median mini-Montreal Cognitive Assessment score was 8 (IQR=4–12). Mean Frailty Index score was 18 (SD=11). Pre-stroke cognitive impairment was apparent in 13/154 (8%) patients. Pre-stroke frailty was significantly associated with lower post-stroke cognition (Standardized-Beta=−0.40; p<0.001) and this association was independent of covariates (Unstandardized-Beta=−0.05; p=0.005). Additional significant variables in the multiple regression model were age (Unstandardized-Beta=−0.05; p=0.002), delirium (Unstandardized-Beta=−2.81; p<0.001), pre-stroke cognitive impairment (Unstandardized-Beta=−2.28; p=0.001), and stroke-severity (Unstandardized-Beta=−0.20; p<0.001). Conclusions: Pre-stroke frailty may be a moderator of post-stroke cognition, independent of other well-established post-stroke cognitive impairment risk factors. (JINS, 2019, 25, 501–506)
We develop a test, based on the Lagrange multiplier [LM] testing principle, for the value of the long memory parameter of a univariate time series that is composed of a fractionally integrated shock around a potentially broken deterministic trend. Our proposed test is constructed from data which are de-trended allowing for a trend break whose (unknown) location is estimated by a standard residual sum of squares estimator applied either to the levels or first differences of the data, depending on the value specified for the long memory parameter under the null hypothesis. We demonstrate that the resulting LM-type statistic has a standard limiting null chi-squared distribution with one degree of freedom, and attains the same asymptotic local power function as an infeasible LM test based on the true shocks. Our proposed test therefore attains the same asymptotic local optimality properties as an oracle LM test in both the trend break and no trend break environments. Moreover, this asymptotic local power function does not alter between the break and no break cases and so there is no loss in asymptotic local power from allowing for a trend break at an unknown point in the sample, even in the case where no break is present. We also report the results from a Monte Carlo study into the finite-sample behaviour of our proposed test.
Recent modelling estimates up to two-thirds of new HIV infections among men who have sex with men occur within partnerships, indicating the importance of dyadic HIV prevention efforts. Although new interventions are available to promote dyadic health-enhancing behaviours, minimal research has examined what factors influence partners’ mutual engagement in these behaviours, a critical component of intervention success. Actor-partner interdependence modelling was used to examine associations between relationship characteristics and several dyadic outcomes theorised as antecedents to health-enhancing behaviours: planning and decision making, communication, and joint effort. Among 270 male-male partnerships, relationship satisfaction was significantly associated with all three outcomes for actors (p = .02, .02, .06 respectively). Latino men reported poorer planning and decision making (actor p = .032) and communication (partner p = .044). Alcohol use was significantly and negatively associated with all outcomes except actors’ planning and decision making (actors: p = .11, .038, .004 respectively; partners: p = .03, .056, .02 respectively). Having a sexual agreement was significantly associated with actors’ planning and decision making (p = .007) and communication (p = .008). Focusing on interactions between partners produces a more comprehensive understanding of male couples’ ability to engage in health-enhancing behaviours. This knowledge further identifies new and important foci for the tailoring of dyadic HIV prevention and care interventions.
Introduction: Smoking is one of the most important risk factors for cardiovascular disease (CVD). Electronic cigarettes (e-cigarettes) are becoming increasingly popular. However, little is known regarding their patterns of use in patients with established CVD.
Aims: We aimed to assess the perceptions and patterns of use of e-cigarettes in patients presenting to a vascular clinic.
Methods: We performed a qualitative study to identify perceptions and beliefs about e-cigarettes. Semi-structured interviews of consecutive patients consenting to participate were performed over five-months. Individuals were recruited from a vascular surgery outpatient clinic. Initial interviews were based on a questionnaire. Further structured interviews were conducted with patients currently using e-cigarettes, which were transcribed and analysed to assess perceptions and patterns of use.
Results/Findings: Four overarching themes emerged: attraction to e-cigarettes as a harm reduction/smoking cessation strategy; uncertainty regarding the risks of e-cigarettes; use of various types of smoking cessation strategies; dual use and often complete relapse to tobacco products.
Conclusions: Patients with established CVD view e-cigarettes as a means of smoking cessation; however, many relapse to tobacco products or use both simultaneously. Further research is necessary regarding the role of e-cigarettes in smoking cessation in this high-risk group.
Dopaminergic imaging has high diagnostic accuracy for dementia with Lewy bodies (DLB) at the dementia stage. We report the first investigation of dopaminergic imaging at the prodromal stage.
We recruited 75 patients over 60 with mild cognitive impairment (MCI), 33 with probable MCI with Lewy body disease (MCI-LB), 15 with possible MCI-LB and 27 with MCI with Alzheimer's disease. All underwent detailed clinical, neurological and neuropsychological assessments and FP-CIT [123I-N-fluoropropyl-2β-carbomethoxy-3β-(4-iodophenyl)] dopaminergic imaging. FP-CIT scans were blindly rated by a consensus panel and classified as normal or abnormal.
The sensitivity of visually rated FP-CIT imaging to detect combined possible or probable MCI-LB was 54.2% [95% confidence interval (CI) 39.2–68.6], with a specificity of 89.0% (95% CI 70.8–97.6) and a likelihood ratio for MCI-LB of 4.9, indicating that FP-CIT may be a clinically important test in MCI where any characteristic symptoms of Lewy body (LB) disease are present. The sensitivity in probable MCI-LB was 61.0% (95% CI 42.5–77.4) and in possible MCI-LB was 40.0% (95% CI 16.4–67.7).
Dopaminergic imaging had high specificity at the pre-dementia stage and gave a clinically important increase in diagnostic confidence and so should be considered in all patients with MCI who have any of the diagnostic symptoms of DLB. As expected, the sensitivity was lower in MCI-LB than in established DLB, although over 50% still had an abnormal scan. Accurate diagnosis of LB disease is important to enable early optimal treatment for LB symptoms.
The Holocene portion of the Siple Dome (Antarctica) ice core was dated by interpreting the electrical, visual and chemical properties of the core. The data were interpreted manually and with a computer algorithm. The algorithm interpretation was adjusted to be consistent with atmospheric methane stratigraphic ties to the GISP2 (Greenland Ice Sheet Project 2) ice core, 10Be stratigraphic ties to the dendrochronology 14 C record and the dated volcanic stratigraphy. The algorithm interpretation is more consistent and better quantified than the tedious and subjective manual interpretation.
Giant ragweed has been increasing as a major weed of row crops in the last 30 yr, but quantitative data regarding its pattern and mechanisms of spread in crop fields are lacking. To address this gap, we conducted a Web-based survey of certified crop advisors in the U.S. Corn Belt and Ontario, Canada. Participants were asked questions regarding giant ragweed and crop production practices for the county of their choice. Responses were mapped and correlation analyses were conducted among the responses to determine factors associated with giant ragweed populations. Respondents rated giant ragweed as the most or one of the most difficult weeds to manage in 45% of 421 U.S. counties responding, and 57% of responding counties reported giant ragweed populations with herbicide resistance to acetolactate synthase inhibitors, glyphosate, or both herbicides. Results suggest that giant ragweed is increasing in crop fields outward from the east-central U.S. Corn Belt in most directions. Crop production practices associated with giant ragweed populations included minimum tillage, continuous soybean, and multiple-application herbicide programs; ecological factors included giant ragweed presence in noncrop edge habitats, early and prolonged emergence, and presence of the seed-burying common earthworm in crop fields. Managing giant ragweed in noncrop areas could reduce giant ragweed migration from noncrop habitats into crop fields and slow its spread. Where giant ragweed is already established in crop fields, including a more diverse combination of crop species, tillage practices, and herbicide sites of action will be critical to reduce populations, disrupt emergence patterns, and select against herbicide-resistant giant ragweed genotypes. Incorporation of a cereal grain into the crop rotation may help suppress early giant ragweed emergence and provide chemical or mechanical control options for late-emerging giant ragweed.
A microchannel plate was used as an ion sensitive detector in a commercial helium ion microscope (HIM) for dark-field transmission imaging of nanomaterials, i.e. scanning transmission ion microscopy (STIM). In contrast to previous transmission HIM approaches that used secondary electron conversion holders, our new approach detects forward-scattered helium ions on a dedicated annular shaped ion sensitive detector. Minimum collection angles between 125 mrad and 325 mrad were obtained by varying the distance of the sample from the microchannel plate detector during imaging. Monte Carlo simulations were used to predict detector angular ranges at which dark-field images with atomic number contrast could be obtained. We demonstrate atomic number contrast imaging via scanning transmission ion imaging of silica-coated gold nanoparticles and magnetite nanoparticles. Although the resolution of STIM is known to be degraded by beam broadening in the substrate, we imaged magnetite nanoparticles with high contrast on a relatively thick silicon nitride substrate. We expect this new approach to annular dark-field STIM will open avenues for more quantitative ion imaging techniques and advance fundamental understanding of underlying ion scattering mechanisms leading to image formation.
We compare observed fluxes from the ultraviolet (IUE) through J and K with recent Kurucz model atmospheres to determine a temperature for the F5 lb supergiant α Per. The two most important advances in this study as compared with previous work are the use of well calibrated ultraviolet fluxes and the use of models with an appropriate microturbulence.
Recent studies suggest that sand can serve as a vehicle for exposure of humans to pathogens at beach sites, resulting in increased health risks. Sampling for microorganisms in sand should therefore be considered for inclusion in regulatory programmes aimed at protecting recreational beach users from infectious disease. Here, we review the literature on pathogen levels in beach sand, and their potential for affecting human health. In an effort to provide specific recommendations for sand sampling programmes, we outline published guidelines for beach monitoring programmes, which are currently focused exclusively on measuring microbial levels in water. We also provide background on spatial distribution and temporal characteristics of microbes in sand, as these factors influence sampling programmes. First steps toward establishing a sand sampling programme include identifying appropriate beach sites and use of initial sanitary assessments to refine site selection. A tiered approach is recommended for monitoring. This approach would include the analysis of samples from many sites for faecal indicator organisms and other conventional analytes, while testing for specific pathogens and unconventional indicators is reserved for high-risk sites. Given the diversity of microbes found in sand, studies are urgently needed to identify the most significant aetiological agent of disease and to relate microbial measurements in sand to human health risk.
The Bovine Respiratory Disease Coordinated Agricultural Project (BRD CAP) is a 5-year project funded by the United States Department of Agriculture (USDA), with an overriding objective to use the tools of modern genomics to identify cattle that are less susceptible to BRD. To do this, two large genome wide association studies (GWAS) were conducted using a case:control design on preweaned Holstein dairy heifers and beef feedlot cattle. A health scoring system was used to identify BRD cases and controls. Heritability estimates for BRD susceptibility ranged from 19 to 21% in dairy calves to 29.2% in beef cattle when using numerical scores as a semi-quantitative definition of BRD. A GWAS analysis conducted on the dairy calf data showed that single nucleotide polymorphism (SNP) effects explained 20% of the variation in BRD incidence and 17–20% of the variation in clinical signs. These results represent a preliminary analysis of ongoing work to identify loci associated with BRD. Future work includes validation of the chromosomal regions and SNPs that have been identified as important for BRD susceptibility, fine mapping of chromosomes to identify causal SNPs, and integration of predictive markers for BRD susceptibility into genetic tests and national cattle genetic evaluations.
To understand the genotypic spectrum of environmental contamination of Staphylococcus aureus in households and its persistence
Prospective longitudinal cohort investigation.
Index participants identified at 2 academic medical centers.
Adults and children with S. aureus skin infections and their household contacts in Los Angeles and Chicago.
Household fomites were surveyed for contamination at baseline and 3 months. All isolates underwent genetic typing.
We enrolled 346 households, 88% of which completed the 3-month follow-up visit. S. aureus environmental contamination was 49% at baseline and 51% at 3 months. Among households with a USA300 methicillin-resistant S. aureus (MRSA) body infection isolate, environmental contamination with an indistinguishable MRSA strain was 58% at baseline and 63% at 3 months. Baseline factors associated with environmental contamination by the index subject’s infection isolate were body colonization by any household member with the index subject’s infection isolate at baseline (odds ratio [OR], 10.93 [95% confidence interval (CI), 5.75–20.79]), higher housing density (OR, 1.47 [95% CI, 1.10–1.96]), and more frequent household fomite cleaning (OR, 1.62 [95% CI, 1.16–2.27]). Household environmental contamination with the index subject’s infection strain at 3 months was associated with USA300 MRSA and a synergistic interaction between baseline environmental contamination and body colonization by any household member with the index subject’s infection strain.
We found that infecting S. aureus isolates frequently persisted environmentally in households 3 months after skin infection. Presence of pathogenic S. aureus strain type in the environment in a household may represent a persistent reservoir that places household members at risk of future infection.
Infect Control Hosp Epidemiol 2014;35(11):1373–1382
The kesterite semiconductor Cu2ZnSnS(e)4 is seen as a suitable absorber layer to replace Cu(In,Ga)Se2 in thin film solar cells, if thin film photovoltaics are to be deployed on the terawatt scale. Currently the best devices, and hence the best kesterite absorber layers are grown away from stoichiometry and are zinc rich and copper poor, presumably leading to the formation of ZnS(e). However, it has been shown that secondary phases present in an absorber layer reduce device performance. If growth in Zn rich conditions seems to be mandatory, then any secondary phases formed should be grown on the surface of the absorber layer so that they may be easily removed by etching. Therefore, it is important to know how and why secondary phases form, and if possible, how to segregate them to the surface of the absorber layer.
Here we show that ZnSe is formed at the initial stages of absorber formation from annealing metal stacks in selenium vapor. Further we demonstrate that the way the precursor metals are distributed on the substrate leads to different absorber layer performances in full devices. The importance of selenium vapor pressure is highlighted in respect to the order of selenisation of the metals, Zn before Cu. Additionally, the importance of selenium and tin selenide vapor pressure during annealing is reviewed with regard to avoiding a decomposition of the Cu2ZnSnSe4 to ZnSe and Cu2Se phases. Regardless of the atmosphere above the absorber, the reaction of the absorber with molybdenum appears unavoidable without the use of a passivation strategy. Counter-intuitively, it is demonstrated that for our absorber layers grown under Zn-rich conditions, removal of the ZnSe is harmful for device performance.
Imputation of moderate-density genotypes from low-density panels is of increasing interest in genomic selection, because it can dramatically reduce genotyping costs. Several imputation software packages have been developed, but they vary in imputation accuracy, and imputed genotypes may be inconsistent among methods. An AdaBoost-like approach is proposed to combine imputation results from several independent software packages, i.e. Beagle(v3.3), IMPUTE(v2.0), fastPHASE(v1.4), AlphaImpute, findhap(v2) and Fimpute(v2), with each package serving as a basic classifier in an ensemble-based system. The ensemble-based method computes weights sequentially for all classifiers, and combines results from component methods via weighted majority ‘voting’ to determine unknown genotypes. The data included 3078 registered Angus cattle, each genotyped with the Illumina BovineSNP50 BeadChip. SNP genotypes on three chromosomes (BTA1, BTA16 and BTA28) were used to compare imputation accuracy among methods, and the application involved the imputation of 50K genotypes covering 29 chromosomes based on a set of 5K genotypes. Beagle and Fimpute had the greatest accuracy among the six imputation packages, which ranged from 0·8677 to 0·9858. The proposed ensemble method was better than any of these packages, but the sequence of independent classifiers in the voting scheme affected imputation accuracy. The ensemble systems yielding the best imputation accuracies were those that had Beagle as first classifier, followed by one or two methods that utilized pedigree information. A salient feature of the proposed ensemble method is that it can solve imputation inconsistencies among different imputation methods, hence leading to a more reliable system for imputing genotypes relative to independent methods.
Testing for the presence of a broken linear trend when the nature of the persistence in the data is unknown is not a trivial problem, because the test needs to be both asymptotically correctly sized and consistent, regardless of the order of integration of the data. In a recent paper, Sayginsoy and Vogelsang (2011, Econometric Theory 27, 992–1025) (SV) show that tests based on fixed-b asymptotics provide a useful solution to this problem in the case where the shocks may be either weakly dependent or display strong dependence within the near-unit-root class. In this paper we analyze the performance of these tests when the shocks may be fractionally integrated, an alternative model paradigm that allows for either weak or strong dependence in the shocks. We demonstrate that the fixed-b trend break statistics converge to well-defined limit distributions under both the null and local alternatives in this case (and retain consistency against fixed alternatives), but that these distributions depend on the fractional integration parameter δ. As a result, it is only when δ is either zero or one that the SV critical values yield correctly sized tests. Consequently, we propose a procedure that employs δ-adaptive critical values to remove the size distortions in the SV test. In addition, use of δ-adaptive critical values also allows us to consider a simplification of the SV test that is (asymptotically) correctly sized across δ but can also provide a significant increase in power over the standard SV test when δ = 1.